7/18/2002 @ 3:47PM

Biotech's Cut-Rate Supercomputer

For years, small biotech companies have used Linux to manage a lot of data on the cheap. Now that looks like a big business opportunity.

Biotechnology companies have been turning to clusters of computers running the Linux operating system to help them manage the weight of data generated by modern biology. Modern approaches to biology, like genomics, which looks for individual genes amidst the clutter of human DNA, or proteomics, which tries to describe some of the most complicated molecules in the body, require sifting through massive amounts of data.

Linux provides a way to build these systems more cheaply than would otherwise be possible. Now, both
IBM
and
Hewlett-Packard
, two of the world’s largest computer companies, are dueling to provide biotech companies–most of which are far from profitable–as well as academic and government institutions with relatively inexpensive supercomputers.

“Linux is an interesting dynamic,” says
Jeffrey
Augen
Jeffrey Augen
, director of life sciences strategy at IBM. “Most of the small biotech companies in the world today are standardizing on Linux platforms and Linux clusters. Small companies, even startup, round-A companies, are coming to us seeking a level of computer horsepower that traditionally you would see in larger companies.”

Focusing on Linux has helped IBM make major strides in life sciences supercomputing. “They’ve been doing a lot of biotech deals, absolutely,” says
Debra
Goldfarb
Debra Goldfarb
, an analyst at
International Data Corp.
who watches life sciences supercomputing. IBM has announced several collaborations: IBM-designed Linux clusters at
Amgen
–the world’s largest biotechnology company–
Inpharmatica
and
Syrrx
rank among the most powerful in the world, according to a list compiled annually by the University of Mannheim and the University of Tennessee.

The market for life sciences supercomputing is small for now: IDC last year estimated the market’s size at $1.2 billion or so. But the company expects it to be ten times bigger by 2004.

For a long time,
Compaq
had the edge in providing supercomputing solutions to biotech companies. The human genome was mapped on parallel computers pieced together from Compaq Alpha servers. But Compaq outsourced the next-generation version of the Alpha chip to Intel (nasdaq: INTC). “HP Compaq is a great story,” says Goldfarb, “but they have to get out of the integration process and move forward.”

For its part, HP is sure that it will eventually look stronger after the merger. “We see a lot of expertise in deploying new systems and consulting on the Compaq side coming together with the systems that we just announced for the Itanium 2 systems developed with Intel,” says
Mike
Balma
Mike Balma
, a Linux business strategist at HP.

Why do biotechnology companies turn to Linux? For one thing, it’s cheap. IBM’s Augen says that a Linux system can cost as little as a tenth of what a more traditional supercomputer would. “We’re comparing a supercomputer that would cost millions of dollars to a Linux cluster that costs in the hundreds of thousands,” he says.

That has made IBM’s Linux systems desirable for small biotech startups that are far from profitability, like
MDS Proteomics
, a division of Toronto’s
MDS
that is studying the way proteins interact, and privately-held
Physiome Sciences
, which is using them to simulate the inner workings of cells.

There is a big difference between the needs of a huge company like a bank or a retail store, which needs to use its computers to do calculations in real time with a low failure rate, and those of a biotech company screening genes or proteins to find new drug targets. If the bank’s computer fails, large sums of money could be lost. That is not true for companies doing scientific research, so long as the machines are capable of making up for any lost time.

“It’s OK if the cluster has to rebooted, because this is research–and downtime of a few minutes isn’t critical,” says Augen. Indeed, in a parallel Linux cluster like the ones used by many biotechnology companies, different groups of computers within the same cluster will be performing different tasks. It’s not necessary for every server to be running optimally all the time.